Agent Skills Hub

trigger-dev-tasks

Expert assistant for designing and optimizing production-grade Trigger.dev background jobs, AI workflows, and resilient asynchronous task architectures in TypeScript.

designer

Expert UI/UX design assistant for React & Next.js. Provides visual critiques, design system architecture, and Tailwind CSS/shadcn/ui implementation guidance for production-grade web applications.

agent-system

Implementation patterns for MERIDIAN autonomous AI agents using Claude API, including BaseAgent lifecycle, structured tool use, token budget enforcement, and cron scheduling.

claude-rag-skills

A suite of professional tools for auditing, evaluating, chunking, and scaffolding production-ready RAG pipelines within Claude Code.

FastMCP Development

Build and manage MCP servers using the FastMCP framework. Guide for creating tools, resources, prompts, Claude Desktop integration, and deployment with Python and TypeScript.

context-bar

A color-coded, real-time context usage progress bar for the Claude Code statusline and manual on-demand checks.

cicd-diagnostics

Diagnose dotCMS CI/CD GitHub Actions failures, including PR builds, merge queue issues, and nightly test reports.

kpi-dashboard-design

Master KPI dashboard design with proven metrics frameworks, SMART goals, and hierarchy patterns to drive business performance from executive insights to operational monitoring.

milan-news-briefing

Automate your daily Milan news digest with this Python-based briefing tool. Supports weather, strikes, world/AI/Italian news, and event scraping, featuring deduplication, RSS/API pipeline management, and AI-agent ready scheduling.

shift-right-testing

Production-grade testing strategy implementing feature flags, canary releases, synthetic monitoring, and chaos engineering for continuous reliability in live environments.

eval-harness

Official evaluation framework for AI agent sessions, implementing Evaluation-Driven Development (EDD) principles to ensure reliability.

evidence-first-debugging

Enforces a strict evidence-based debugging workflow using structured observation, hypothesis testing, and causality validation to eliminate speculation in technical investigations.